Effect of financial development and technological innovation on green growth—Analysis based on spatial Durbin model

Cao, Jianhong; Law, Siong Hook; Samad, Abdul Rahim Bin Abdul; Mohamad, Wan Norhidayah Binti W; Wang, Jianlong; Yang, Xiaodong

doi:10.1016/j.jclepro.2022.132865

Cited by 157 publications

(51 citation statements)

References 61 publications

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“…According to Figure 4 , the number of provinces with high-level coupling and coordination of green finance and industrial-structure optimization in China showed a fluctuating upward trend, but the distribution was relatively scattered, showing a “fragmented” distribution characteristic dominated by the east. This is similar to the research conclusion that economic centers such as Beijing and Shanghai are more conducive to the coupling and coordination of economic factors [ 71 ]. In terms of the change in the number of provinces, the number of high-level-coupling and -coordination provinces was changed to 3 (2013) → 2 (2015) → 3 (2017) → 7 (2019), and the average value of the coupling and coordination degree corresponding to the second level also showed a fluctuating upward trend of 0.408 (2013) → 0.413 (2015) → 0.407 (2017) → 0.427 (2019).…”

Section: Resultssupporting

confidence: 88%

“…From the perspective of the regional gap, the interval and standard deviation showed a trend of first decreasing and then increasing, reflecting that the coupling and coordination of various regions were “agglomeration → equilibrium → agglomeration”. Cao et al (2022) believe that a good financial structure can provide power for an economic operation, effectively attract capital inflows to increase regional investment opportunities, form a “capital agglomeration” effect, and help realize a virtuous cycle of economic development [ 71 ]. From 2012 to 2016, the regional coupling coordination degree decreased from 0.067 to 0.049, and the standard deviation also decreased from 0.161 to 0.142, indicating that the coordination of green finance and industrial-structure optimization in various regions transitioned from agglomeration to equilibrium, the regional gap weakened, and most regions were still in the primary coordination stage.…”

Section: Resultsmentioning

confidence: 99%

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Coupling and Coordinative Development of Green Finance and Industrial-Structure Optimization in China: Spatial-Temporal Difference and Driving Factors

Nie

Chen

Liu

et al. 2022

IJERPH

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Although the literature has studied the direction and extent of the effect of green finance on industrial-structure optimization, quantitative analysis of the coupling coordination and spatial–temporal differences between green finance and industrial structure is relatively scarce. Therefore, in this paper, we built the theoretical framework of the coupling coordination relationship between green finance and industrial-structure optimization, and then we used the coupling coordination degree and geographic detector model to investigate the spatial–temporal evolution characteristics and influencing factors of the coupling coordination between the two based on the panel data of 31 provinces from 2012 to 2019. The results show that China’s green finance and industrial-structure optimization have basically reached the primary coupling, and the coupling coordination degree is from 0.40 to 0.43, which shows a “W”-type fluctuation trend of recovery. The regional gap of the coupling coordination degree firstly decreased and then increased, showing a change law of “agglomeration, equilibrium and agglomeration”. In the spatial dimension, the high-level coordination region showed an increasing trend of “fragmentation” fluctuation, while the low-level coordination region concentrated in the central and western regions with a tendency of “low value locking”. The trend surface showed a spatial characteristic of “high in the north and low in the south–high in the east and west and low in the middle”. We also found that the dependence of foreign trade and technological innovation are the main factors affecting the coupling coordination degree, and the interaction between government support and human capital synergistic is the crucial channel for the coevolution of green finance and industrial structure to promote green and low-carbon development.

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Section: Resultssupporting

confidence: 88%

Section: Resultsmentioning

confidence: 99%

Coupling and Coordinative Development of Green Finance and Industrial-Structure Optimization in China: Spatial-Temporal Difference and Driving Factors

Nie

Chen

Liu

et al. 2022

IJERPH

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show abstract

“…It means that an increase in the FD enhances GG in China. A similar nexus between FD and GG is reported by Cao et al (2022). The short-run findings define that the REC impact on GG is reported significantly positive at all quantiles, except 0.80 to 0.95.…”

Section: Constant Ecmsupporting

confidence: 75%

Pro-environmental behavior–Renewable energy transitions nexus: Exploring the role of higher education and information and communications technology diffusion

2022

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The most accepted solution to deal with the problems of global warming and climate change is to transform the energy sector by moving toward renewable energy. Therefore, the primary focus of the analysis is to examine the role of renewable energy consumption, higher education, and ICT in improving environmental quality and green growth in China. We have employed the quantile ARDL model to obtain the short-and long-run estimates. According to the findings of QARDL, the long-run estimated coefficients of renewable energy consumption and higher education are positively significant in most quantiles. However, in the long run, the estimates attached to ICT are insignificant in the CO2 emissions model in most quantiles. On the other hand, the estimates of renewable energy consumption are significantly positive from the 50th quantile and onward in the green growth model, confirming that the higher the renewable energy in the economy, closer it will get to the target of green economic growth. The long-run estimates of higher education and ICT are positively significant at most quantiles in the green growth model. In the short run, renewable energy consumption turned out to be the most critical determinant of CO2 emissions and green growth.

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“…Income inequality is determined through the GINI index. The control variables are selected based on previous green growth literature [ 27 , 39 ]. Secondary school enrolment is taken to measure education.…”

Section: Model and Methodsmentioning

confidence: 99%

[Retracted] Does Income Inequality Harm Green Growth? The BRICS Experience

Chen

Tang

2022

Journal of Environmental and Public Health

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Green growth plays a vital role in ensuring sustainable development. Managing economic growth without disrupting the environment is considered the need of the present time. Therefore, the empirics have turned their attention toward finding the determinants of green growth. Hence, we aim to investigate the impact of income inequality on green growth in BRICS economies from 1993 to 2020. Findings of the panel autoregressive distributed lag (ARDL) model confirm that the long-run estimate attached to GINI is negatively significant, implying that higher inequality in the BRICS economies lowers the rate of green growth. The country-wise results highlighted the negative impact of GINI on green growth in India and China only and insignificant in other countries. In the short run, the estimates are inconclusive and mixed, be it group-wise or individual estimates. Our findings imply that the target of lower inequality and environmental sustainability can be achieved simultaneously.

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Effect of financial development and technological innovation on green growth—Analysis based on spatial Durbin model

Cited by 157 publications

References 61 publications

Coupling and Coordinative Development of Green Finance and Industrial-Structure Optimization in China: Spatial-Temporal Difference and Driving Factors

Coupling and Coordinative Development of Green Finance and Industrial-Structure Optimization in China: Spatial-Temporal Difference and Driving Factors

Pro-environmental behavior–Renewable energy transitions nexus: Exploring the role of higher education and information and communications technology diffusion

[Retracted] Does Income Inequality Harm Green Growth? The BRICS Experience

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